Image reconstruction from signals received by sensor arrays is used in many application fields, including radio interferometry, e.g., for astronomical investigations, magnetic resonance imaging, ultrasound imaging and positron emission tomography for medical applications. Iterative reconstruction typically refers to algorithms used to reconstruct 2D and 3D images. Often, iterative reconstruction techniques provide better results but are computationally more expensive.
Image reconstruction techniques often require to estimate parameters. In turn, an efficient parameter estimation typically relies on a convex optimization using linear programming algorithms, or maximization of a posterior probability distribution. This is for instance the case for image reconstruction methods using signals received from sensors in many application fields, such as radio interferometry for astronomical investigations, and magnetic resonance imaging, ultrasound imaging, and positron emission tomography for medical applications.